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研究生:陳侃如
研究生(外文):Kan-Ru Chen
論文名稱:用於非正向虹膜取像之可操控傾斜式影像感測器
論文名稱(外文):Steerable Skew Image Sensor for Non-orthogonal View Iris Imaging
指導教授:石勝文石勝文引用關係
指導教授(外文):Sheng-Wen Shih
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:43
中文關鍵詞:虹膜辨識自動對焦影像感測器非正向虹膜取像
外文關鍵詞:iris recognitionauto-focusingimage sensornon-orthogonal view iris imaging
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生物辨識技術已經被廣泛的研究,其中虹膜辨識技術更是極受歡迎的研究主題,許多
先前的研究奠定了虹膜辨識的基礎,研究各種虹膜定位與特徵抽取的方法,無非是要提昇虹
膜辨識的準確度。而針對靜態影像資料的分析,雖然可能已經有極高的辨識率,但是拿到人
機互動環境下卻不一定能表現的一樣好,因為實際應用的互動環境下總是帶來新考驗。本
論文即是探討要如何不需讓使用者配合仍能取得高品質的虹膜影像。使用者不需要是有經
驗的使用者甚至不需移動即可自動拍到清晰的虹膜影像供虹膜辨識使用。在這個研究中我
們設計了一個可操控傾斜式影像感測器,裝置在三個自由度的機構上面,可以自由操控前
後位置以及旋轉角度。利用自動對焦演算法分析影像後移動影像感測器到最佳位置,取得
清晰影像。最後的實驗分析了各種不同對焦演算法的特性,並且展現了可自由旋轉的影像
感測器可以有效的改善影像清晰度。
Biometric teniques have been studied extensively and iris recognition has become one
of the most popular resear topics. Prior-researes have focused on the iris localization
and feature extraction methods to increase the recognition rate whi have become the base
of current iris recognition systems. Although the methods developed based on a static iris
database usually can aieve very high recognition rate, the may not perform as well in a
dynamic environment as the static environment. In a real application, the dynamic input video
always bring up new allenges. is resear is focused on how to acquire high quality
images for iris recognition with less user cooperation. erefore, users neither need to be
experienced in using this system nor have to adjust their head pose to input their iris image.
In this study we developed a steerable skew image sensor aaed to a three degrees of freedom
meanism that controls the position and rotation of the focus plane. By using auto-focusing
teniques, we can move the image sensor to the best focused position to acquire a high quality
iris image. In the experiments, we analyzed the propriety of various auto-focusing algorithms
and showed that the steerable skew image sensor can effectively enhance the image quality.
第一章緒論....................................................................................................................................... 9
1.1 生物辨識技術. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.2 相關研究. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.2.1 虹膜辨識技術. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.2.2 影像修復技術. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.2.3 自動對焦技術. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3 研究動機. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.4 研究目標與方法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.5 論文組織架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
第二章系統架構............................................................................................................................... 14
2.1 虹膜辨識系統流程. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2 攝影機模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.1 透鏡成像原理. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.2 可控制傾斜式影像感測器. . . . . . . . . . . . . . . . . . . . . . . . 16
第三章對焦尺度演算法................................................................................................................... 19
3.1 簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.2 影像梯度能量. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.3 影像拉普拉斯能量. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.4 影像絕對中心矩. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.5 高通濾波後的影像絕對中心矩. . . . . . . . . . . . . . . . . . . . . . . . . . 23
第四章自動對焦演算法................................................................................................................... 24
4.1 自動對焦原理. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
4.2 全域搜尋. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.3 多階段全域搜尋. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.4 爬山搜尋法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.5 規則為主的搜尋法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
第五章實驗....................................................................................................................................... 31
第六章結論....................................................................................................................................... 39
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